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Bibliographic Details
Main Author: Komarov, Pavel
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2506.06210
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author Komarov, Pavel
author_facet Komarov, Pavel
contents One of the happiest accidents in all math is the ease of transforming a function to and taking derivatives in the Fourier frequency domain. But in order to exploit this extraordinary fact without serious artefacting, and in order to be able to use a computer, we need quite a bit of extra knowledge and care. This document sets out the math behind the spectral-derivatives Python package. I touch on fundamental signal processing and calculus concepts as necessary and build upwards.
format Preprint
id arxiv_https___arxiv_org_abs_2506_06210
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Spectral Derivatives
Komarov, Pavel
Signal Processing
History and Overview
One of the happiest accidents in all math is the ease of transforming a function to and taking derivatives in the Fourier frequency domain. But in order to exploit this extraordinary fact without serious artefacting, and in order to be able to use a computer, we need quite a bit of extra knowledge and care. This document sets out the math behind the spectral-derivatives Python package. I touch on fundamental signal processing and calculus concepts as necessary and build upwards.
title Spectral Derivatives
topic Signal Processing
History and Overview
url https://arxiv.org/abs/2506.06210